An Indexed Bibliography of Genetic Algorithms in Power ... - CiteSeerX

An Indexed Bibliography of Genetic Algorithms in Power Engineering compiled by

Jarmo T. Alander Department of Information Technology and Industrial Management University of Vaasa P.O. Box 700 FIN-65101 Vaasa Finland e-mail: [email protected] phone: 358-61-3248 444 fax: 358-61-3248 467 Report Series No. 94-1-POWER

DRAFT March 2, 1995

c 1995 Jarmo T. Alander Copyright

Trademarks Product and company names listed are trademarks or trade names of their respective companies.

Warning While this bibliography has been compiled with the utmost care, the editor takes no responsibility for any errors, missing information, the contents or quality of the references, nor for the usefulness and/or the consequences of their application. The fact that a reference is included in this publication does not imply a recommendation. The use of any of the methods in the references is entirely at the user's own responsibility. Especially the above warning applies to those references that are marked by trailing y(or *), which are the ones that the editor has unfortunately not had the opportunity to read. An abstract was available of the references marked with *.

Contents 1 Preface

1.1 How to get this report via Internet? 1.2 Acknowledgement

1 : : : : : : : : : : : : : : : : : : : : : : : : : : : : :

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2 Statistical summaries 2.1 2.2 2.3 2.4 2.5

Publication type Annual distribution Classi cation Authors Conclusions and future

3 3

5

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3 Indexes

3.1 Books 3.2 Journal articles 3.3 Theses 3.3.1 PhD theses 3.3.2 Master's theses 3.4 Report series 3.5 Patents 3.6 Crossreferences 3.7 Authors 3.8 Subject index 3.9 Annual index: 1957-1994

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9

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4 Permuted title index Bibliography Appendixes A Abbreviations B Bibliography entry formats

9 9 9 9 9 9 9 10 11 12 13

15 19 23 23 25

i

List of Tables 1.1 Queries used to extract this subbibliography from the main one. 2.1 2.2 2.3 2.4

: : : : : : : : : : : : : :

Distribution of publication type. Annual distribution of contributions. The most popular subjects. The most productive genetic algorithms in power engineering authors.

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ii

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1 5 5 5 6

List of Figures 2.1 The number of genetic algorithms in power engineering.

iii

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6

iv

Chapter 1

Preface \Living organism are consummate problem solvers. They exhibit a versatility that puts the best computer programs to shame." [1] John H. Holland

The material of this bibliography has been extracted from the genetic algorithm bibliography [2], which currently contains over 3000 items and which has been collected from several sources of genetic algorithm literature including Usenet newsgroup comp.ai.genetic and the bibliographies [3, 4, 5, 6]. The following index periodicals have been used systematically  ACM: ACM Guide to Computing Literature: 1979 { 1993/4  CCA: Computer & Control Abstracts: Jan. 1992 { Dec. 1994  CTI: Current Technology Index Jan./Feb. 1993 { Jan./Feb. 1994  DAI: Dissertation Abstracts International: Vol. 53 No. 1 { Vol. 55 No. 4 (1994)  EEA: Electrical & Electronics Abstracts: Jan. 1991 { Dec. 1994  P: Index to Scienti c & Technical Proceedings: Jan. 1986 { Feb. 1995 (except Nov. 1994)  EI A: The Engineering Index Annual: 1987 { 1992  EI M: The Engineering Index Monthly: Jan. 1993 { Dec. 1994 The following GA researchers have already kindly supplied their complete autobibliographies and/or proofread references to their papers: Dan Adler, Patrick Argos, Jarmo T. Alander, James E. Baker, Wolfgang Banzhaf, Ralf Bruns, I. L. Bukatova, Thomas Back, Yuval Davidor, Dipankar Dasgupta, Marco Dorigo, Bogdan Filipic, Terence C. Fogarty, David B. Fogel, Toshio Fukuda, Hugo de Garis, Robert C. Glen, David E. Goldberg, Martina Gorges-Schleuter, Jerey Horn, Aristides T. Hatjimihail, Mark J. Jakiela, Richard S. Judson, Akihiko Konagaya, Aaron Konstam, John R. Koza, Kristinn Kristinsson, D. P. Kwok, Carlos B. Lucasius, Michael de la Maza, John R. McDonnell, J. J. Merelo, Laurence D. Merkle, Zbigniew Michalewics, Melanie Mitchell, David J. Nettleton, Volker Nissen, Nicholas J. Radclie, Colin R. Reeves, David Rogers, Ivan Santiban~ez-Koref, Marc Schoenauer, Markus Schwehm, Hans-Paul Schwefel, Michael T. Semertzidis, William M. Spears, Donald S. Szarkowicz, El-Ghazali Talbi, Leigh Tesfatsion, Peter M. Todd, Jari Vaario, Gilles Venturini, Hans-Michael Voigt, Roger L. Wainwright , Steward W. Wilson, Xin Yao, and Xiaodong Yin . The table 1.1 gives the queries that have been used to extract this bibliography. string

engineering /power Power

eld

class Power engineering Power engineering journal article

ANNOTE JOURNAL

Table 1.1: Queries used to extract this subbibliography from the main one. 1

2 This bibliography is updated on a regular basis and certainly contains many errors and inconsistences. The editor would be glad to hear from any reader who notices any errors, missing information, articles etc. In the future a more complete version of this bibliography will be prepared for the genetic algorithms in power engineering research community and others who are interested in this rapidly growing area of genetic algorithms.

How to get this report via Internet?

3

1.1 How to get this report via Internet? Versions of this bibliography are available via anonymous ftp and www from the following sites: media country site directory le Finland ftp.uwasa.fi /cs/report94-1 gaPOWERbib.ps.Z Finland http://www.cs.hut.fi ~ja/gaPOWERbib gaPOWERbib.html

ftp www

Observe that these versions may be somewhat dierent and perhaps reduced as compared to this volume that you are now reading.

1.2 Acknowledgement The editor wants to acknowledge all who have kindly supplied references, papers and other information on genetic algorithms in power engineering literature. The editor also wants to acknowledge Elizabeth Heap-Talvela for her kind proofreading of the manuscript of this bibliography.

4

Chapter 2

Statistical summaries 2.2 Annual distribution

This chapter gives some general statistical summaries of genetic algorithms in power engineering literature. More detailed indexes can be found in the next chapter.

Table 2.2 gives the number of genetic algorithms in power engineering papers published annually. The annual distribution is also shown in g. 2.1. The average annual growth of GA papers has been approximately 40 % during almost the last twenty years.

References to each engineering area are listed below:

 Power engineering 44 references ([7]-[50])  Power engineering journal article 5 re-

year items year items 1978 1 1979 0 1980 0 1981 0 1982 1 1983 0 1984 0 1985 1 1986 0 1987 1 1988 0 1989 0 1990 1 1991 4 1992 4 1993 17 1994 18 1995 1 total 49

ferences ([51]-[55])

Observe that each reference is included (by the computer) only to one class (see also the queries for classi cation in table 1.1).

2.1 Publication type This bibliography contains published contributions including reports and patents. All unpublished manuscripts have been omitted unless accepted for publication. In addition theses, PhD, MSc etc., are also included whether or not published somewhere. Table 2.1 gives the distribution of publication type of the whole bibliography. Observe that the number of journal articles may also include articles published or to be published in unknown forums.

Table 2.2: Annual distribution of contributions.

2.3 Classi cation Every bibliography item has been given at least one describing keyword or classi cation by the editor of this bibliography. Keywords occurring most are shown in table 2.3.

type number of items part of a collection 1 journal article 24 proceedings article 20 report 2 PhD thesis 1 MSc thesis 1 total 49

engineering /power 41 optimization 5 CAD 5 others 99

Table 2.3: The most popular subjects.

Table 2.1: Distribution of publication type. 5

6

2.4 Authors

Table 2.4 gives the most productive authors. total number of authors 86 1 author 4 4 authors 3 8 authors 2 72 authors 1

Table 2.4: The most productive genetic algorithms in power engineering authors.

6

Genetic algorithms in power engineering 1000

d d d d d

number of annual papers (log scale) 100

10 d

d

dd d d d

1 dd d 1960

dd d d d d d d dd d dd d d dd d d

t

tt tt

t t t t

1970 year 1980

1990

-

t

Figure 2.1: The number of genetic algorithms in power engineering ()  = total GA papers.

Conclusions and future

2.5 Conclusions and future

7

The editor believes that this bibliography contains references to most genetic algorithms in power engineering contributions upto and including the year 1994 and the editor hopes that this bibliography could give some help to those who are working or planning to work in this rapidly growing area of genetic algorithms.

8

Chapter 3

Indexes 3.1 Books

3.3 Theses

The following two lists contain theses, rst PhD theses and then Master's etc. theses, arranged in alphabetical order by the name of the school.

The following list contains all items classi ed as books. 

none

3.3.1 PhD theses

3.2 Journal articles

Case Western Reserve University,

The following list contains the references to every journal article included in this bibliography. The list is arranged in alphabetical order by the name of the journal.

3.3.2 Master's theses

[23]

This list includes also \Dimplomarbeit", \Tech. Lic. Theses", etc. Auburn University,

Electr. Power Syst. Res. (Switzerland), Electric Power Systems Research, IEE Proc., Gener. Transm. Distrib. (UK), IEE Proceedings, Generation, Transmission and Distrib. (UK), IEEE Transaction on Power Systems, IEEE Transactions of Power Delivery, IEEE Transactions on Energy Conversion, IEEE Transactions on Power Delivery, IEEE Transactions on Power Systems, Intelligent Systems Engineering, International Journal of Electrical Power Energy Systems (UK), Journal of Computing in Civil Engineering, Journal of Engineering for Power, Journal of Wind Engineering and Industrial Aerodynamics, [21]

[32]

[52]

3.4 Report series

[8]

The following list contains references to all papers published as technical reports. The list is arranged in alphabetical order by the name of the institute.

[13, 24]

[12]

[34]

[15]

Linkoping University, Technische Universitat der Berlin,

[51]

[29]

[22, 31, 53, 54]

[41]

total 2 reports in 2 institutes

[40]

3.5 Patents

[30]

[35]

The following list contains the names of the patents of genetic algorithms in power engineering. The list is arranged in alphabetical order by the name of the patent.

[55]

[19]

Proc. CSEE (China), Transactions of the ASME, Transactions of the Institute of Electrical Engineers of Japan B, Transactions of the Institute of Electrical Engineers of Japan C, total 24 articles in 18 journals [10, 16]

[36]



[9, 38]

[45]

9

none

10

3.6 Crossreferences

The following table contains the references to the proceedings having genetic algorithms in power engineering articles and references to these articles. in [56], in [57], in [58],

[17, 18] [49] [48]

Authors

11

3.7 Authors

The following list contains all genetic algorithms in power engineering authors and references to their known contributions. Adermann, H.-J., Akimoto, Y., Axelsson, Jakob, Bakirtzis, A. G., Bakirtzis, A., Boone, G., Chiang, Hsiao-Dong, Chu, K. H., Dasgupta, Dipankar, Dinjiang, Huang, Diviacco, B., El-Hawary, M. E., Fukuyama, Y., Fushuan, Wen, Germay, Noel, Goldberg, David E., Gregory, B. A., Haida, T., Heine, Steen, Horiguchi, T., Iba, Kenji, Inoue, T., Inuiguchi, M., Ishihara, Toshihisa, Izui, Y., Jinjiang, Yu, Kazarlis, S., Kazarlis, Spyros, Kazarlis, Syros A., Kierman, L., Kitagawa, Minoru, Kuo, Chie Hsiung, Kurosaka, S., Lai, L. L., Lansberry, John E., Liutao, Wei, Ma, J. T., Maifeld, T. T., Markwich, P., McGregor, Douglas R., Menth, Stefan, Miyamoto, Y., Miyatake, T., Mori, Hiroyuki, Mori, Y., Mosetti, G., Nara, Koichi, Ndeh-Che, F., Neumann, Ingo, Pahwa, Anil, Parks, G. T., Petridis, V.,

Poloni, C., Poon, P. W., Qingchuan, Zeng, Rahman, Saifur, Richards, G. G., Richards, Gill G., Sakawa, M., Satoh, T., Semmler, Klaus, Sheble, G. B., Sheble, Gerald B., Shiose, Atsushi, Shiromaru, I., Sonnenschein, H., Suginohara, N., Sundhararajan, Srinivasan, Swarup, K. S., Takeda, K., Tiebing, Jiang, Tong, Siu Shing, Ueki, Y., Utaka, J., Walters, David C., Warwick, Kevin, Wong, K. P., Wong, Y. W., Wozniak, L., Wright, Ted, Wu, Q. H., Yang, Hanqing Q., Yang, H., Yin, Xiaodong, Yoshimi, M., Zhenxiang, Han,

[19]

[48] [16] [54]

[34] [51]

[26] [27] [28, 29] [25] [8, 7] [30] [30] [14] [24, 33] [16] [19] [31] [9] [10] [52] [35] [36] [27] [11]

[49] [46] [28]

[21] [31] [53] [49]

[55] [49] [22]

[37] [42] [16]

[36] [9] [49]

[31, 32] [40]

[13]

[43, 44]

[13]

[12, 38, 39]

[15]

[49]

[23]

[49]

[17, 20]

[53]

[51]

[37] [16] [7] [8] [25] [40] [46, 53, 47] [35] [45] [14] [15] [16] [17, 20] [21] [41] [24] [28] [45] [45] [18, 42, 43, 44] [45] [19] [46, 53, 47] [14] [11] [22] [48] [8, 7, 25]

[34] [52, 50]

[37] [10]

total 49 articles by 86 dierent authors

12

3.8 Subject index

All subject keywords of the papers given by the editor of this bibliography are shown next. The keywords \neural networks", \optimization", and \evolution strategies" have been omitted in this list because of their high occurrence rate. CAD, classic, coal red power plant, coding, comparison simulated annealing, control adaptive, exhaust emissions, generator excitation, power dispatch, controllers PI, dispatch problem, engineering aerospace, electric power, electrical, energy, nuclear, power,

[36, 28, 29, 30, 51] [35] [45] [31]

[53, 48, 10]

[15] [45] [14] [17]

[15] [13]

[23] [51] [55, 53] [55] [48] [41, 26, 35, 36, 27, 32, 46, 42, 43, 48,

28, 29, 30, 31, 33, 34, 37, 38, 39, 40, 44, 45, 47, 49, 50, 7, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25]

power /dispatch, power /fault section estimation, power supplies, expert systems, fault diagnosis, fuzzy systems, 100, implementation C, FORTRAN77, load forecasting, NOx, population size 100, pressurised water reactor, review AI in electric power system, scheduling, SGA, topological observability, turbines wind, unit commitment, unit commitment problem, [8]

[10]

[23]

[21]

[40, 10] [49] [31]

[31]

[53]

[11]

[45]

[28, 31] [48]

[54]

[52, 49, 23]

[31]

[18]

[19]

[16, 21, 24, 25] [7]

Annual index: 1957-1994

3.9 Annual index: 1957-1994

The following table gives references to the contributions published during the period 1957-1994. 1978, 1982, 1985, 1987, 1990, 1991, 1992, 1993, 1994, 1995,

[41] [55] [26] [35] [36] [27, 32, 52, 46] [42, 43, 53, 48] [28, 29, 30, 31, 33, 51, 34, 37, 38, 39, 40, 44, 45, 47, 54, 49, 50] [7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24] [25]

13

14

Chapter 4

Permuted title index

[40] [15] [40] [39] [10] [16] [9] [32] [17] [50] [54] [36] [55] [55] [22] [30] [41] [7] [16] [26] [33] [26] [26] [47] [48] [42] [34] [51] [28] [14] [48] [36] [29]

The words of the titles of the articles are shown in the next table arranged in alphabetical order. The most common words have been excluded. The key word is shown by a disk () in the title eld with the exception that it is omitted when appearing as the rst word of the title after shown keyword. The other abbreviation used to compress titles are shown in appendix A. Adaptive alarm processor for fault diagnosis on power transmission networks  hydrogenerator governor tuning with a GA alarm Adaptive  processor for fault diagnosis on power transmission networks allocation Opt. VAr  by GA annealing Fault section estimation in power syst. using GA and simulated  application A new heuristic GA and its  in solution of the unit commitment { An  of GA to service restoration in distr. syst. { An  of GAs to the economic dispatch of power generation  of evol. prog. to opt. reactive power dispatch  of GAs to multiple load ow solution problem in electrical power syst. Arti cial intelligence in electric power syst. : a survey of the Japanese industry { Turbine preliminary design using  and numerical opt. balance A modular opt. calculation method of power station energy  and plat eciency calculation A modular opt.  method of power station energy balance and plat eciency capacitors Opt. sel. of  for radial distributions syst. using a GA capasitor Opt.  placement in distribution syst. by GA Clausius-Rankine-Prozesses Der thermische Wasserstrahlanrieb auf der Grundlage des oenen  commitment A GA solution to the unit  problem { A new heuristic GA and its appl. in solution of the unit  { Treatment of integral contingent conditions in optimum power plant  { Unit  in thermal power generation using GAs conditions Treatment of integral contingent  in optimum power plant commitment contingent Treatment of integral  conditions in optimum power plant commitment copper Distribution syst.  and iron loss minimization by GA core Opt. PWR reload  design decomposition Power syst.  using a simulated evol. technique design Distribution syst. harmonic worst case  using a GA { Distribution-syst. harmonic worst-case  using a GA { GAs in industrial  { Modelling,  and simulation of generator excitation syst. by using object-oriented techniques and GAs { Opt. PWR reload core  { Turbine preliminary  using arti cial intelligence and numerical opt. { Turbine preliminary  using GAs

[40] [32] [17] [8] [13] [20] [37] [44] [43] [9] [53] [34] [30] [47] [46] [22] [51] [45] [44] [43] [32] [8] [13] [37] [31] [55] [54] [18] [50] [55] [10] [42] [11] [17] [14] [21] [40] [10] [50] [52] [49]

15

diagnosis Adaptive alarm processor for fault  on power transmission networks dispatch An appl. of GAs to the economic  of power generation { Appl. of evol. prog. to opt. reactive power  { GA solution to the economic  problem { Gen. and gen. /simulated-annealing appr. to economic  { Gen. search for opt. reactive power  of power syst. { Opt. economic power  using GAs dispatching A GA based appr. to economic load  { A method for economic load  using a GA distributed An appl. of GA to service restoration in  syst. distribution Impl. of GA for  syst. loss minimum re-con guration  syst. harmonic worst case design using a GA { Opt. capasitor placement in  syst. by GA Distribution systems copper and iron loss minimization by GA  loss minimum re-con guration by GA distributions Opt. sel. of capacitors for radial  syst. using a GA Distribution-system harmonic worst-case design using a GA dynamic A parameter tuning for  simulation of power plants using GAs economic A GA based appr. to  load dispatching { A method for  load dispatching using a GA { An appl. of GAs to the  dispatch of power generation { GA solution to the  dispatch problem { Gen. and gen. /simulated-annealing appr. to  dispatch { Opt.  power dispatch using GAs economic-dispatch GA solution of  with valve point loading eciency A modular opt. calculation method of power station energy balance and plat  electric Arti cial intelligence in  power syst. : a survey of the Japanese industry electric power A GA-based method for opt. topological observability index in  networks electrical Appl. of GAs to multiple load ow solution problem in  power syst. energy A modular opt. calculation method of power station  balance and plat eciency estimation Fault section  in power syst. using GA and SA evolution Power syst. decomposition using a simulated  technique evolutionary Opt. load forecast models using an  alg. evolutionary programming Appl. of  to opt. reactive power dispatch excitation Modelling, design and simulation of generator  syst. by using object-oriented techniques and GAs expert system Unit commitment by GA and  fault Adaptive alarm processor for  diagnosis on power transmission networks  section estimation in power syst. using GA and SA

ow Appl. of GAs to multiple load  solution problem in electrical power syst. { Investigations on solving the load  problem by GAs fuzzy Hot parts operating schedule of gas turbines by GAs and  satis cing methods

16 [18] [49] [32] [33] [14] [13] [15] [41] [34] [51] [16] [49] [15] [53] [18] [28] [54] [26] [52] [47] [54] [44] [43] [50] [52] [11] [31] [47] [46] [53] [19] [18] [55] [43] [49] [47] [46] [53] [14] [55] [18] [40] [36] [14] [18] [49] [17] [20]

GA-based A  method for opt. topological observability index in electric power networks gas turbines Hot parts operating schedule of  by GAs and fuzzy satis cing methods generation An appl. of GAs to the economic dispatch of power  { Unit commitment in thermal power  using GAs generator Modelling, design and simulation of  excitation syst. by using object-oriented techniques and GAs genetic/simulated-annealing Gen. and  appr. to economic dispatch governor Adaptive hydrogenerator  tuning with a GA Grundlage Der thermische Wasserstrahlanrieb auf der  des oenen Clausius-Rankine-Prozesses harmonic Distribution syst.  worst case design using a GA { Distribution-syst.  worst-case design using a GA heuristic A new  GA and its appl. in solution of the unit commitment Hot parts operating schedule of gas turbines by GAs and fuzzy satis cing methods hydrogenerator Adaptive  governor tuning with a GA Implementation of GA for distribution syst. loss minimum re-con guration index A GA-based method for opt. topological observability  in electric power networks industrial GAs in  design industry Arti cial intelligence in electric power syst. : a survey of the Japanese  integral Treatment of  contingent conditions in optimum power plant commitment Investigations on solving the load ow problem by GAs iron Distribution syst. copper and  loss minimization by GA Japanese Arti cial intelligence in electric power syst. : a survey of the  industry load A GA based appr. to economic  dispatching { A method for economic  dispatching using a GA { Appl. of GAs to multiple  ow solution problem in electrical power syst. { Investigations on solving the  ow problem by GAs load forecast models Opt.  using an evol. alg. loading GA solution of economic-dispatch with valve point  loss Distribution syst. copper and iron  minimization by GA { Distribution syst.  minimum re-con guration by GA { Impl. of GA for distribution syst.  minimum recon guration means Opt. of wind turbine positioning in large windfarms by  of GA method A GA-based  for opt. topological observability index in electric power networks { A modular opt. calculation  of power station energy balance and plat eciency { A  for economic load dispatching using a GA methods Hot parts operating schedule of gas turbines by GAs and fuzzy satis cing  minimization Distribution syst. copper and iron loss  by GA minimum Distribution syst. loss  re-con guration by GA { Impl. of GA for distribution syst. loss  recon guration Modelling design and simulation of generator excitation syst. by using object-oriented techniques and GAs modular A  opt. calculation method of power station energy balance and plat eciency networks A GA-based method for opt. topological observability index in electric power  { Adaptive alarm processor for fault diagnosis on power transmission  numerical Turbine preliminary design using arti cial intelligence and  opt. object-oriented Modelling, design and simulation of generator excitation syst. by using  techniques and GAs observability A GA-based method for opt. topological  index in electric power networks operating Hot parts  schedule of gas turbines by GAs and fuzzy satis cing methods optimal Appl. of evol. prog. to  reactive power dispatch { Gen. search for  reactive power dispatch of power syst.

[30] [37] [22] [39] [55] [27] [35] [19] [12] [36] [18] [11] [48] [26] [45] [35] [30] [38] [26] [55] [31] [19] [23] [55] [40] [32] [17] [50] [54] [10] [20] [42] [37] [12] [38] [26] [33] [45] [7] [50] [8] [52] [40] [48] [22] [17] [20] [12] [38] [46] [53] [48] [23] [9] [49] [49] [23]

capasitor placement in distribution syst. by GA economic power dispatch using GAs sel. of capacitors for radial distributions syst. using a GA  VAr allocation by GA optimization A modular  calculation method of power station energy balance and plat eciency { GAs appr. to voltage  { GAs in pipeline   of wind turbine positioning in large windfarms by means of GA { Reactive power  by GA { Turbine preliminary design using arti cial intelligence and numerical  optimizing A GA-based method for  topological observability index in electric power networks  load forecast models using an evol. alg.  PWR reload core design optimum Treatment of integral contingent conditions in  power plant commitment parameter A  tuning for dynamic simulation of power plants using GAs pipeline GAs in  opt. placement Opt. capasitor  in distribution syst. by GA planning Reactive power  in large power syst. using GAs plant Treatment of integral contingent conditions in optimum power  commitment plat A modular opt. calculation method of power station energy balance and  eciency point GA solution of economic-dispatch with valve  loading positioning Opt. of wind turbine  in large windfarms by means of GA power A GA appr. to sch. resources for a space  syst. { A modular opt. calculation method of  station energy balance and plat eciency { Adaptive alarm processor for fault diagnosis on  transmission networks { An appl. of GAs to the economic dispatch of  generation { Appl. of evol. prog. to opt. reactive  dispatch { Appl. of GAs to multiple load ow solution problem in electrical  syst. { Arti cial intelligence in electric  syst. : a survey of the Japanese industry { Fault section estimation in  syst. using GA and SA { Gen. search for opt. reactive  dispatch of  syst.  syst. decomposition using a simulated evol. technique { Opt. economic  dispatch using GAs { Reactive  opt. by GA { Reactive power planning in large  syst. using GAs { Treatment of integral contingent conditions in optimum  plant commitment { Unit commitment in thermal  generation using GAs power plants A parameter tuning for dynamic simulation of  using GAs problem A GA solution to the unit commitment  { Appl. of GAs to multiple load ow solution  in electrical power syst. { GA solution to the economic dispatch  { Investigations on solving the load ow  by GAs processor Adaptive alarm  for fault diagnosis on power transmission networks PWR Opt.  reload core design radial Opt. sel. of capacitors for  distributions syst. using a GA reactive Appl. of evol. prog. to opt.  power dispatch { Gen. search for opt.  power dispatch of power syst.  power opt. by GA Reactive power planning in large power syst. using GAs re-con guration Distribution syst. loss minimum  by GA { Impl. of GA for distribution syst. loss minimum  reload Opt. PWR  core design resources A GA appr. to sch.  for a space power syst. restoration An appl. of GA to service  in distr. syst. satis cing Hot parts operating schedule of gas turbines by GAs and fuzzy  methods schedule Hot parts operating  of gas turbines by GAs and fuzzy satis cing methods scheduling A GA appr. to  resources for a space power syst.   

Permuted title index [20] [10] [22] [9] [10] [42] [45] [14] [7] [25] [16] [50] [31] [8] [52] [23] [55] [54] [14] [24] [33] [41] [18] [40] [26] [45] [15] [36] [29] [19] [7] [16] [33] [21] [24] [25] [31] [39] [27] [41] [19] [19] [34] [51]

search Gen.  for opt. reactive power dispatch of power syst. section Fault  estimation in power syst. using GA and SA selection Opt.  of capacitors for radial distributions syst. using a GA service An appl. of GA to  restoration in distr. syst. simulated Fault section estimation in power syst. using GA and  annealing { Power syst. decomposition using a  evol. technique simulation A parameter tuning for dynamic  of power plants using GAs { Modelling, design and  of generator excitation syst. by using object-oriented techniques and GAs solution A GA  to the unit commitment problem { A GA  to the unit commitment problem { A new heuristic GA and its appl. in  of the unit commitment { Appl. of GAs to multiple load ow  problem in electrical power syst. { GA  of economic-dispatch with valve point loading { GA  to the economic dispatch problem solving Investigations on  the load ow problem by GAs space A GA appr. to sch. resources for a  power syst. station A modular opt. calculation method of power  energy balance and plat eciency survey Arti cial intelligence in electric power syst. : a  of the Japanese industry techniques Modelling, design and simulation of generator excitation syst. by using object-oriented  and GAs Thermal unit commitment using GAs { Unit commitment in  power generation using GAs thermische Der  Wasserstrahlanrieb auf der Grundlage des oenen Clausius-Rankine-Prozesses topological A GA-based method for opt.  observability index in electric power networks transmission Adaptive alarm processor for fault diagnosis on power  networks Treatment of integral contingent conditions in optimum power plant commitment tuning A parameter  for dynamic simulation of power plants using GAs { Adaptive hydrogenerator governor  with a GA Turbine preliminary design using arti cial intelligence and numerical opt.  preliminary design using GAs { Opt. of wind  positioning in large windfarms by means of GA unit A GA solution to the  commitment problem { A new heuristic GA and its appl. in solution of the  commitment  commitment in thermal power generation using GAs Unit commitment by GA and expert syst. { Thermal  using GAs unit commitment problem A GA solution to the  valve GA solution of economic-dispatch with  point loading VAr Opt.  allocation by GA voltage GAs appr. to  opt. Wasserstrahlanrieb Der thermische  auf der Grundlage des oenen Clausius-Rankine-Prozesses wind Opt. of  turbine positioning in large windfarms by means of GA windfarms Opt. of wind turbine positioning in large  by means of GA worst Distribution syst. harmonic  case design using a GA worst-case Distribution-syst. harmonic  design using a GA

17

18

Bibliography [1] John H. Holland. Genetic algorithms. Scienti c American, 267(1):44{50, 1992. ga:Holland92a. [2] Jarmo T. Alander. An indexed bibliography of genetic algorithms: Years 1957-1993. Art of CAD Ltd., Vaasa (Finland), 1994. (over 3000 GA references). [3] David E. Goldberg, Kelsey Milman, and Christina Tidd. Genetic algorithms: A bibliography. IlliGAL Report 92008, University of Illinois at Urbana-Champaign, 1992. ga:Goldberg92f. [4] N. Saravanan and David B. Fogel. A bibliography of evolutionary computation & applications. Technical Report FAU-ME-93-100, Florida Atlantic University, Department of Mechanical Engineering, 1993. (available via anonymous ftp cite magenta.me.fau.edu directory /pub/ep-list/bib le EC-ref.ps.Z) ga:Fogel93c. [5] Thomas Back. Genetic algorithms, evolutionary programming, and evolutionary strategies bibliographic database entries. (personal communication) ga:Back93bib, 1993. [6] Thomas Back, Frank Homeister, and Hans-Paul Schwefel. Applications of evolutionary algorithms. Technical Report SYS-2/92, University of Dortmund, Department of Computer Science, 1992. ga:Schwefel92d. [7] S. Kazarlis, A. Bakirtzis, and V. Petridis. A genetic algorithm solution to the unit commitment problem. In Proceedings of the IEEE PES Winter 94-95 Meeting, page ?, ?, ? 1994. IEEE, New York. (accepted for publication in)y(Petridis) ga94Kazarlis. [8] A. Bakirtzis, V. Petridis, and Spyros Kazarlis. Genetic algorithm solution to the economic dispatch problem. IEE Proc., Gener. Transm. Distrib. (UK), 141(4):377{382, July 1994. (available via anonymous ftp cite elecserv directory /pub le dispatch.ps.Z) ga94aBakirtzis. [9] Y. Fukuyama and Y. Ueki. An application of genetic algorithm to service restoration in distributed system. Transactions of the Institute of Electrical Engineers of Japan B, 114-B(4):361{366, April 1994. (in Japanese)y(EEA 78080/94) ga94aFukuyama. [10] Wen Fushuan and Han Zhenxiang. Fault section estimation in power systems using genetic algorithm and simulated annealing. Proc. CSEE (China), 14(3):29{35, May 1994. (in Chinese)y(EI M172021/94 EEA 77822/94) ga94aFushuan. [11] Steen Heine and Ingo Neumann. Optimizing load forecast models using an evolutionary algorithm. In Proceedings of the Second European Congress on Intelligent Techniques and Soft Computing (EUFIT'94), volume 3, pages 1690{1694, Aachen (Germany), 20.-23. September 1994. ELITE-Foundation. ga94aHeine. [12] Kenji Iba. Reactive power optimization by genetic algorithm. IEEE Transaction on Power Systems, 9(2):685{692, May 1994. ga94aIba. [13] K. P. Wong and Y. W. Wong. Genetic and genetic/simulated-annealing approaches to economic dispatch. IEE Proceedings, Generation, Transmission and Distrib. (UK), 141(5):507{513, September 1994. ga94aKPWong. [14] L. L. Lai, F. Ndeh-Che, and K. H. Chu. Modelling, design and simulation of generator excitation system by using objectoriented techniques and genetic algorithms. In ?, editor, Proceedings of the First International Power Electronics and Motion Control Conference (IPEMC'94), volume 2, pages 1099{1104, Beijing (China), 27.-30. June 1994. International Academic Publishers, Beijing (China). y(EEA 100079/94) ga94aLai. [15] John E. Lansberry and L. Wozniak. Adaptive hydrogenerator governor tuning with a genetic algorithm. IEEE Transactions on Energy Conversion, 9(1):179{185, March 1994. ga94aLansberry. [16] Wei Liutao, Zeng Qingchuan, Jiang Tiebing, Yu Jinjiang, and Huang Dinjiang. A new heuristic genetic algorithm and its application in solution of the unit commitment. Proc. CSEE (China), 14(2):67{72, March 1994. (in Chinese)y(EEA 53701/94) ga94aLiutao. [17] J. T. Ma and Q. H. Wu. Application of evolutionary programming to optimal reactive power dispatch. In Proceedings of the First IEEE Conference on Evolutionary Computation [56], pages 730{735. ga94aMa. [18] Hiroyuki Mori. A GA-based method for optimizing topological observability index in electric power networks. In Proceedings of the First IEEE Conference on Evolutionary Computation [56], pages 565{568. ga94aMori. [19] G. Mosetti, C. Poloni, and B. Diviacco. Optimization of wind turbine positioning in large windfarms by means of genetic algorithm. Journal of Wind Engineering and Industrial Aerodynamics, 51(1):105{116, January 1994. y(EI M089713/94 CC ET et AS Vol. 25 No. 14 /94) ga94aMosetti. [20] Q. H. Wu and J. T. Ma. Genetic search for optimal reactive power dispatch of power systems. In International Conference on Control'94, volume 1, pages 717{722, Coventry (UK), 21.-24. March 1994. IEE, London. y(CCA 53057/94) ga94aQHWu.

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In Proceedings of the IEEE Power Engineering Winter Meeting, volume ?, page ?, New York, January 1995. IEEE, New York. (available via anonymous ftp cite elecserv.eng.auth.gr directory /pub le unitcom.ps.Z) ga95aKazarlis. [26] H.-J. Adermann. Treatment of integral contingent conditions in optimum power plant commitment. In H. J. Wacker, editor, Applied Optimization Techniques in Energy Problems, pages 1{18. Teubner, Stuttgart, 1985. y([6]) ga:Adermann85. [27] T. Haida and Y. Akimoto. Genetic algorithms approach to voltage optimization. In M. A. El-Sharkawi and R. J. Marks, editors, Proceedings of the First International Forum on Applications of Neural Networks to Power Systems (ANNPS'91), pages 139{143, Seattle, WA, 23.-26. July 1991. IEEE, New York. y(CCA 20368/93 EEA 26255/93) ga:Akimoto91. [28] Jakob Axelsson, Stefan Menth, and Klaus Semmler. Genetic algorithms in industrial design. In Proceedings, Fifth International Conference on Tools with Arti cial Intelligence TAI'93, pages 64{67, Boston, MA, 8.-11. November 1993. IEEE Computer Society Press, Los Alamitos, CA. ga:Axelsson93a. [29] Jakob Axelsson. Turbine preliminary design using genetic algorithms. Technical Report LiTH-IDA-Ex-9302, Linkoping University, Sweden, 1993. ga:Axelsson93b. [30] G. Boone and Hsiao-Dong Chiang. Optimal capasitor placement in distribution systems by genetic algorithm. International Journal of Electrical Power Energy Systems (UK), 15(3):155{162, June 1993. y(EEA 58103/93 EI 093088/94) ga:Boone93a. [31] David C. Walters, Gerald B. Sheble, and M. E. El-Hawary. Genetic algorithm solution of economic-dispatch with valve point loading. IEEE Transactions on Power Systems, 8(3):1325{1332, 1993. (Proceedings of the 1992 Summer Meeting of the Power-Engineering-Society of IEEE, Seattle, WA, 12.-16. Jul. 1992) ga:DCWalters93a. [32] David C. Walters. An application of genetic algorithms to the economic dispatch of power generation. Master's thesis, Auburn University, 1991. y(Walters93a) ga:DCWaltersMSthesis. [33] Dipankar Dasgupta. Unit commitment in thermal power generation using genetic algorithms. In P. W. H. Chung, G. Lovegrove, and M. Ali, editors, Proceedings of the Sixth International Conference on Industrial & Engineering Applications of Arti cial Intelligence and Expert Systems (IEA/AIE-93), pages 374{383, Edinburgh, Scotland, 1.4. June 1993. Gordon and Breach Science, Langhorne. y(P62941/95) ga:Dasgupta93a. [34] G. G. Richards and H. Yang. Distribution system harmonic worst case design using a genetic algorithm. IEEE Transactions of Power Delivery, 8(3):1484{1491, July 1993. ga:GGRichards93a. [35] David E. Goldberg and Chie Hsiung Kuo. Genetic algorithms in pipeline optimization. Journal of Computing in Civil Engineering, 1(2):128{141, April 1987. ga:Goldberg87i. [36] Siu Shing Tong and B. A. Gregory. Turbine preliminary design using arti cial intelligence and numerical optimization. Transactions of the ASME, 90-GT-148(?):?, ? 1990. y(Axelsson90a) ga:Gregory90a. [37] M. Yoshimi, K. S. Swarup, and Y. Izui. Optimal economic power dispatch using genetic algorithms. In Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems (ANNPS'93), pages 157{162, Yokohama (Japan), April 1993. IEEE, New York. y(EEA 24770/94) ga:Izui93a. [38] Kenji Iba. Reactive power planning in large power systems using genetic algorithms. Transactions of the Institute of Electrical Engineers of Japan B, 113-B(8):865{872, August 1993. (in Japanese)y(EEA 24858/94) ga:KIba93b. [39] Kenji Iba. Optimal VAr allocation by genetic algorithm. In Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems (ANNPS'93), pages 163{168, Yokohama (Japan), April 1993. IEEE, New York. y(EEA 24861/94) ga:KIba93c. [40] L. Kierman and Kevin Warwick. Adaptive alarm processor for fault diagnosis on power transmission networks. Intelligent Systems Engineering, 2(1):25{37, 1993. y(EI M106851/93 EEA 52391/93) ga:KWarwick93b. [41] P. Markwich. Der thermische Wasserstrahlanrieb auf der grundlage des oenen Clausius-Rankine-Prozesses. Technical report, Technische Universitat der Berlin, 1978. y(BackBib) ga:Markwich78. [42] Hiroyuki Mori and K. Takeda. Power system decomposition using a simulated evolution technique. In Proceedings of the Second International Conference on Automation, Robotics and Computer Vision (ICARCV'92), volume 3, pages INV 11.2/1{5, Singapore, 16.-18. September 1992. Nanyang Technol. University, Singapore. y(CCA 18640/93 EEA 24734/94) ga:Mori92a. [43] Hiroyuki Mori and T. Horiguchi. A method for economic load dispatching using a genetic algorithm. In Proceedings of the Second International Conference on Automation, Robotics and Computer Vision (ICARCV'92), volume 3, pages INV 11.4/1{5, Singapore, 16.-18. September 1992. Nanyang Technol. University, Singapore. y(EEA 24736/94) ga:Mori92b.

University of Vaasa, Finland

21

[44] Hiroyuki Mori and T. Horiguchi. A genetic algorithm based approach to economic load dispatching. In Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems (ANNPS'93), pages 145{150, Yokohama (Japan), April 1993. IEEE, New York. y(Mori93a EEA 24770/94) ga:Mori93b. [45] Y. Miyamoto, T. Miyatake, S. Kurosaka, and Y. Mori. A parameter tuning for dynamic simulation of power plants using genetic algorithms. Transactions of the Institute of Electrical Engineers of Japan C, 113-D(12):1410{1415, December 1993. (in Japanese)y(EEA 60089/94 CCA 57025/94) ga:Mori93c. [46] Koichi Nara, T. Satoh, and Minoru Kitagawa. Distribution systems loss minimum re-con guration by genetic algorithm. In ?, editor, Proceedings of the 3rd Conference on Expert Systems Application to Power Systems, pages 724{730, ?, ? 1991. ? y([?]) ga:Nara91a. [47] Koichi Nara and Minoru Kitagawa. Distribution systems copper and iron loss minimization by genetic algorithm. In Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems (ANNPS'93), pages 151{156, Yokohama (Japan), April 1993. IEEE, New York. y(EEA 24913/94) ga:Nara93a. [48] P. W. Poon and G. T. Parks. Optimizing PWR reload core design. In Manner and Manderick [58], pages 371{380. ga:Poon92a. [49] M. Sakawa, J. Utaka, M. Inuiguchi, I. Shiromaru, N. Suginohara, and T. Inoue. Hot parts operating schedule of gas turbines by genetic algorithms and fuzzy satis cing methods. In IJCNN'93 [57], pages 746{749. ga:Sakawa93a. [50] Xiaodong Yin. Application of genetic algorithms to multiple load ow solution problem in electrical power systems. In Proceedings of the 32nd IEEE Conference on Decision and Control, volume 4, pages 3734{3738, San Antonio, TX, 15.-17. December 1993. IEEE Control Systems Society. ga:Yin93a. [51] Gill G. Richards and Hanqing Q. Yang. Distribution-system harmonic worst-case design using a genetic algorithm. IEEE Transactions on Power Delivery, 8(3):1484{1491, 1993. (in Proceedings of 1992 Summer Meeting of IEEE / Power-Engineering-Society, Seattle, WA, 12.-16. Jul.) ga:GGRichards92b. [52] Xiaodong Yin and Noel Germay. Investigations on solving the load ow problem by genetic algorithms. Electric Power Systems Research, 22(3):151{163, December 1991. ga:Germay91a. [53] Koichi Nara, Atsushi Shiose, Minoru Kitagawa, and Toshihisa Ishihara. Implementation of genetic algorithm for distribution systems loss minimum re-con guration. IEEE Transactions on Power Systems, 7(3):1044{1051, August 1992. ga:Nara92a. [54] Saifur Rahman. Arti cial intelligence in electric power systems: a survey of the Japanese industry. IEEE Transactions on Power Systems, 8(3):1211{1218, August 1993. ga:Rahman93a. [55] H. Sonnenschein. A modular optimization calculation method of power station energy balance and plat eciency. Journal of Engineering for Power, 104(?):255{259, 1982. y(BackBib) ga:Sonnenschein82a. [56] IEEE. Proceedings of the First IEEE Conference on Evolutionary Computation, volume 2, Orlando, FL, 27.-29. June 1994. IEEE. ga94ICCIEC2. [57] IJCNN'93-NAGOYA Proceedings of 1993 International Joint Conference on Neural Networks, Nagoya (Japan), 25.29. October 1993. IEEE. ga:IJCNN93. [58] R. Manner and B. Manderick, editors. Parallel Problem Solving from Nature, 2, Brussels, 28.-30. September 1992. Elsevier Science Publishers, Amsterdam. ga:PPSN2.

22

Notations

y(ref) = the bibliography item does not belong to my collection of genetic papers. (ref) = citation source code. ACM = ACM Guide to Computing Literature, EEA = Electrical & Electronics Abstracts, CCA = Computers & Control Abstracts, CTI = Current Technology Index, EI = The Engineering Index (A = Annual, M = Monthly), DAI = Dissertation Abstracts International, P = Index to Scienti c & Technical Proceedings, BackBib = Thomas Back's unpublished bibliography, Fogel/Bib = David Fogel's EA bibliography, etc * = only abstract seen. ? = data of this eld is missing (BiBTeX-format). The last eld in each reference item in Teletype font is the BiBTEXkey of the corresponding reference.

Appendix A

Abbreviations

The following other abbreviations were used to compress the titles of articles in the permutation title index: 23

24 AI Alg. AL ANN(s) Appl. Appr. Cntr. Coll. Comb. Conf. CS(s) Distr. Eng. EP ES Evol. ExS(s) FF(s) GA(s) Gen. GP Ident. Impl. Int. ImPr JSS ML Nat. NN(s) Opt. OR Par. Perf. Pop. Proc. Prog. Prob. QAP Rep. SA Sch. Sel. Symp. Syst. Tech. TSP

= Arti cial Intelligence = Algorithm(s) = Arti cial Life = Arti cial Neural Net(work)(s) = Application(s), Applied = Approach(es) = Control, Controlled, Controlling, Controller(s) = Colloquium = Combinatorial = Conference = Classi er System(s) = Distributed = Engineering = Evolutionary Programming = Evolutionsstrategie(n), Evolution(ary) strategies = Evolution, Evolutionary = Expert System(s) = Fitness Function(s) = Genetic Algorithm(s) = Genetic(s), Genetical(ly) = Genetic Programming = Identi cation = Implementation(s) = International = Image Processing = Job Shop Scheduling = Machine Learning = Natural = Neural Net(work)(s) = Optimization, Optimal, Optimizer(s), Optimierung = Operation(s) Research = Parallel, Parallelism = Performance = Population(s), Populational(ly) = Proceedings = Programming, Program(s), Programmed = Problem(s) = Quadratic Assignment Problem = Representation(s), Representational(ly) = Simulated Annealing = Scheduling, Schedule(s) = Selection, Selectionism = Symposium = System(s) = Technical, Technology = Travel(l)ing Salesman Problem

Appendix B

Bibliography entry formats This documentation was prepared with LATEX and reproduced from camera-ready copy supplied by the editor. The ones who are familiar with BibTeX may have noticed that the references are printed using abbrv bibliography style and have no diculties in interpreting the entries. For those not so familiar with BibTeX are given the following formats of the most common entry types. The optional elds are enclosed by "[ ]" in the format description. Unknown elds are shown by "?". y after the entry means that neither the article nor the abstract of the article was available for reviewing and so the reference entry and/or its indexing may be more or less incomplete.

Book

Author(s), Title, Publisher, Publisher's address, year.

Example John H. Holland. Adaptation in Natural and Arti cial Systems. The University of Michigan Press, Ann Arbor, 1975.

Journal article

Author(s), Title, Journal, volume(number): rst page { last page, [month,] year.

Example David E. Goldberg. Computer-aided gas pipeline operation using genetic algorithms and rule learning. Part I: Genetic algorithms in pipeline optimization. Engineering with Computers, 3(?):35{45, 1987. y.

Note: the number of the journal unknown, the article has not been seen. Proceedings article

Author(s), Title, editor(s) of the proceedings, Title of Proceedings, [volume,] pages, location of the conference, date of the conference, publisher of the proceedings, publisher's address.

Example John R. Koza. Hierarchical genetic algorithms operating on populations of computer programs. In N. S. Sridharan, editor, Eleventh International Joint Conference on Arti cial Intelligence (IJCAI-89), pages 768{774, Detroit, MI, 20.-25. August 1989. Morgan Kaufmann, Palo Alto, CA. y.

Technical report

Author(s), Title, type and number, Institute, year.

Example 25

26 Thomas Back, Frank Homeister, and Hans-Paul Schwefel. Applications of evolutionary algorithms. Technical Report SYS-2/92, University of Dortmund, Department of Computer Science, 1992.